A defining characteristic of the modern industrial society is the complexity of business processes that are involved in the production and delivery to market of almost every type of goods or services that are available today. Large or complex business processes are involved in the production and delivery of diverse products ranging, for example, from energy, health care, food, automobiles, sundry goods, telecommunications, music and other media. The business processes are complex not merely because of the physical size of the supply chain to market, but because of the complex array of decision-making variables that can affect production and delivery. For example, in the electric power industry, utility plant operating engineers and managers are faced with a complex array of decision making variables,—arising from deregulated markets, technology change, multiple weather events, physical failure situations and supply anomalies, and now the specter of terrorist attacks across multiple power grids. The variables have impacts of varying scale, e.g., local or global, short term or long term, on the business process. Further, the impact of each variable in real time may be dependent on the state of the other variables.
Conventional systems and methods for supporting decision-making deal with complexity in the business process by treating the business process in fragments. The business process is partitioned by organizational parts or divisions, and by hierarchal levels (e.g., regulatory control, supervisory control, and strategic planning). For example, regulatory control is used at a low level to tactically control local process variables. At the next higher level, supervisory control is used, for example, to optimize production schedules and to co-ordinate activities of different parts of the business process. Scheduling, operation planning, and capacity planning, or strategy functions, which may affect the business process on longer time scales, are carried out at even higher hierarchical levels. The business process decisions made at each level are often supported in isolation on the basis of ad hoc assumptions or static models of the process conditions at the other levels or of the state of other variables at that level. The fragmented approach to the complexity of the business processes can lead to gaps, and missed synergies or common mode interactions, which can affect the efficiency and security of the business process. While the fragmented approach for dealing with complexity may be adequate in static business environments, it does not exploit the potential for real time decision making support that is made possible by increasing investments in computerization and automation of the business processes.
Consideration is now being given to improving prior art systems and methods for business decision support. Attention is particularly directed to integrating supervisory and regulatory control as well as higher level strategy control for decision making under uncertainty in real time. Attention is also directed to integrating real option valuations in the decision making process.